Matplotlib.dates.DateFormatter class in Python
Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
Matplotlib.dates.DateFormatter
The matplotlib.dates.DateFormatter
class is used to format a tick (in seconds since the epoch) with a string of strftime format. Its base class is matplotlib.ticker.Formatter
.
Syntax: class matplotlib.dates.DateFormatter(fmt, tz=None)
Parameters:
- fmt: It accepts a strftime format string for formatting and is a required argument.
- tz: It holds information regarding the timezone. If set to none it ignores the timezone information while formatting of the date string.
Example 1:
import numpy
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas
total_bars = 25
numpy.random.seed(total_bars)
dates = pandas.date_range( '3/4/2020' ,
periods = total_bars,
freq = 'm' )
diff = pandas.DataFrame(
data = numpy.random.randn(total_bars),
index = dates,
columns = [ 'A' ]
)
figure, axes = plt.subplots(figsize = ( 10 , 6 ))
axes.xaxis.set_major_formatter(mdates.DateFormatter( '%Y-%m' ))
axes.bar(diff.index,
diff[ 'A' ],
width = 25 ,
align = 'center' )
|
Output:
Example 2:
import matplotlib
import matplotlib.pyplot as plt
from datetime import datetime
origin = [ '2020-02-05 17:17:55' ,
'2020-02-05 17:17:51' ,
'2020-02-05 17:17:49' ]
a = [datetime.strptime(d, '%Y-%m-%d %H:%M:%S' ) for d in origin]
b = [ '35.764299' , '20.3008' , '36.94704' ]
x = matplotlib.dates.date2num(a)
formatter = matplotlib.dates.DateFormatter( '%H:%M:%S' )
figure = plt.figure()
axes = figure.add_subplot( 1 , 1 , 1 )
axes.xaxis.set_major_formatter(formatter)
plt.setp(axes.get_xticklabels(), rotation = 15 )
axes.plot(x, b)
plt.show()
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Output:
Last Updated :
21 Apr, 2020
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